{smcl}
{com}{sf}{ul off}{txt}{.-}
       log:  {res}G:\ISQ\g�_rn_jkr_ISQ_replication.smcl
  {txt}log type:  {res}smcl
 {txt}opened on:  {res} 7 Aug 2008, 16:13:18
{txt}
{com}. use "G:\ISQ\g�_rn_jkr_ISQ_replication.dta"
{txt}
{com}. do "C:\DOCUME~1\Ragnhild\LOCALS~1\Temp\STD01000000.tmp"
{txt}
{com}. 
. * REPLICATION DATA FOR GUDRUN �STBY, RAGNHILD NORD�S & JAN KETIL R�D
. * REGIONAL INEQUALITIES AND CIVIL CONFLICT IN SUB-SAHARAN AFRICA 
. * INTERNATIONAL STUDIES QUARTERLY
. 
. set more off
{txt}
{com}. 
. *** TABLE 1
. * Model 1
. logit onset_use lag_ln_dist2cic lag_ln_dist2cinc intbnd dia_sec peton_use pop_use_ln ethdiff ///
>   peaceyrs _spline*, robust cl(gwno)

{txt}Iteration 0:   log pseudolikelihood = {res}-684.30126
{txt}Iteration 1:   log pseudolikelihood = {res}-663.95334
{txt}Iteration 2:   log pseudolikelihood = {res}-628.08245
{txt}Iteration 3:   log pseudolikelihood = {res}-625.59329
{txt}Iteration 4:   log pseudolikelihood = {res}-625.53629
{txt}Iteration 5:   log pseudolikelihood = {res}-625.53625

{txt}Logistic regression                               Number of obs   = {res}      6208
                                                  {txt}Wald chi2({res}11{txt})   = {res}     69.15
                                                  {txt}Prob > chi2     = {res}    0.0000
{txt}Log pseudolikelihood = {res}-625.53625                 {txt}Pseudo R2       = {res}    0.0859

                                  {txt}(Std. Err. adjusted for {res}22{txt} clusters in gwno)
{hline 13}{c TT}{hline 64}
             {c |}               Robust
   onset_use {c |}      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
{hline 13}{c +}{hline 64}
lag_ln_di~ic {c |}  {res} .0094689   .0628763     0.15   0.880    -.1137664    .1327043
{txt}lag_ln_di~nc {c |}  {res}-.0777955    .038163    -2.04   0.041    -.1525936   -.0029974
      {txt}intbnd {c |}  {res}-.1996842   .3564567    -0.56   0.575    -.8983265    .4989581
     {txt}dia_sec {c |}  {res} .7475882   .2726734     2.74   0.006     .2131582    1.282018
   {txt}peton_use {c |}  {res} .6656912   .4822738     1.38   0.167    -.2795481     1.61093
  {txt}pop_use_ln {c |}  {res} .0049815   .1623266     0.03   0.976    -.3131728    .3231358
     {txt}ethdiff {c |}  {res} .0682954   .3509069     0.19   0.846    -.6194695    .7560604
    {txt}peaceyrs {c |}  {res} .1612656    .169574     0.95   0.342    -.1710934    .4936246
    {txt}_spline1 {c |}  {res} .0049368   .0028347     1.74   0.082    -.0006191    .0104927
    {txt}_spline2 {c |}  {res}-.0027942   .0024875    -1.12   0.261    -.0076695    .0020811
    {txt}_spline3 {c |}  {res}  .000209   .0014791     0.14   0.888      -.00269     .003108
       {txt}_cons {c |}  {res}-2.530105   2.379248    -1.06   0.288    -7.193346    2.133136
{txt}{hline 13}{c BT}{hline 64}

{com}. 
. * Model 2 
. logit onset_use lag_ln_dist2cic lag_ln_dist2cinc intbnd dia_sec peton_use pop_use_ln ethdiff  ///
>   peaceyrs _spline* asset, robust cl(gwno) 

{txt}Iteration 0:   log pseudolikelihood = {res}-684.30126
{txt}Iteration 1:   log pseudolikelihood = {res} -666.1714
{txt}Iteration 2:   log pseudolikelihood = {res}-626.87216
{txt}Iteration 3:   log pseudolikelihood = {res}-624.15598
{txt}Iteration 4:   log pseudolikelihood = {res}-624.09444
{txt}Iteration 5:   log pseudolikelihood = {res}-624.09439

{txt}Logistic regression                               Number of obs   = {res}      6208
                                                  {txt}Wald chi2({res}12{txt})   = {res}    103.39
                                                  {txt}Prob > chi2     = {res}    0.0000
{txt}Log pseudolikelihood = {res}-624.09439                 {txt}Pseudo R2       = {res}    0.0880

                                  {txt}(Std. Err. adjusted for {res}22{txt} clusters in gwno)
{hline 13}{c TT}{hline 64}
             {c |}               Robust
   onset_use {c |}      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
{hline 13}{c +}{hline 64}
lag_ln_di~ic {c |}  {res} .0102795   .0647169     0.16   0.874    -.1165633    .1371223
{txt}lag_ln_di~nc {c |}  {res}-.0717735   .0454424    -1.58   0.114    -.1608389    .0172919
      {txt}intbnd {c |}  {res}-.2819542   .2889126    -0.98   0.329    -.8482124    .2843041
     {txt}dia_sec {c |}  {res} .7173938   .2739022     2.62   0.009     .1805554    1.254232
   {txt}peton_use {c |}  {res} .6463709   .4130994     1.56   0.118    -.1632891    1.456031
  {txt}pop_use_ln {c |}  {res}-.0175641   .1454788    -0.12   0.904    -.3026973    .2675692
     {txt}ethdiff {c |}  {res} .0765301   .3606483     0.21   0.832    -.6303276    .7833878
    {txt}peaceyrs {c |}  {res} .1797536   .1576364     1.14   0.254    -.1292082    .4887153
    {txt}_spline1 {c |}  {res} .0050847   .0028525     1.78   0.075    -.0005061    .0106755
    {txt}_spline2 {c |}  {res}-.0028017   .0025013    -1.12   0.263    -.0077042    .0021008
    {txt}_spline3 {c |}  {res} .0001555   .0014568     0.11   0.915    -.0026998    .0030107
       {txt}asset {c |}  {res}-1.425226   2.767399    -0.52   0.607    -6.849229    3.998776
       {txt}_cons {c |}  {res}-2.010731   1.976549    -1.02   0.309    -5.884695    1.863233
{txt}{hline 13}{c BT}{hline 64}

{com}. 
. * Model 3
. logit onset_use lag_ln_dist2cic lag_ln_dist2cinc intbnd dia_sec peton_use pop_use_ln ethdiff ///
>   peaceyrs _spline* education, robust cl(gwno) 

{txt}Iteration 0:   log pseudolikelihood = {res}-684.30126
{txt}Iteration 1:   log pseudolikelihood = {res}-672.72608
{txt}Iteration 2:   log pseudolikelihood = {res}-594.82752
{txt}Iteration 3:   log pseudolikelihood = {res}-589.28992
{txt}Iteration 4:   log pseudolikelihood = {res}-589.09215
{txt}Iteration 5:   log pseudolikelihood = {res}-589.09175

{txt}Logistic regression                               Number of obs   = {res}      6208
                                                  {txt}Wald chi2({res}12{txt})   = {res}    216.84
                                                  {txt}Prob > chi2     = {res}    0.0000
{txt}Log pseudolikelihood = {res}-589.09175                 {txt}Pseudo R2       = {res}    0.1391

                                  {txt}(Std. Err. adjusted for {res}22{txt} clusters in gwno)
{hline 13}{c TT}{hline 64}
             {c |}               Robust
   onset_use {c |}      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
{hline 13}{c +}{hline 64}
lag_ln_di~ic {c |}  {res} .0248285   .0524992     0.47   0.636     -.078068     .127725
{txt}lag_ln_di~nc {c |}  {res}-.0789918    .037372    -2.11   0.035    -.1522396    -.005744
      {txt}intbnd {c |}  {res}-.5242171    .314596    -1.67   0.096    -1.140814    .0923797
     {txt}dia_sec {c |}  {res} .6344264   .2344698     2.71   0.007      .174874    1.093979
   {txt}peton_use {c |}  {res} .7277428   .2683373     2.71   0.007     .2018113    1.253674
  {txt}pop_use_ln {c |}  {res} .0209594   .1341632     0.16   0.876    -.2419957    .2839145
     {txt}ethdiff {c |}  {res} .1050047   .3720429     0.28   0.778    -.6241859    .8341953
    {txt}peaceyrs {c |}  {res} .3238865   .1434615     2.26   0.024     .0427071     .605066
    {txt}_spline1 {c |}  {res} .0060219   .0025734     2.34   0.019     .0009782    .0110657
    {txt}_spline2 {c |}  {res}-.0025175    .002254    -1.12   0.264    -.0069352    .0019002
    {txt}_spline3 {c |}  {res}-.0005201   .0013549    -0.38   0.701    -.0031757    .0021356
   {txt}education {c |}  {res}-.3952296   .0934966    -4.23   0.000    -.5784795   -.2119797
       {txt}_cons {c |}  {res}-2.195993   2.044745    -1.07   0.283     -6.20362    1.811633
{txt}{hline 13}{c BT}{hline 64}
Note: 3 failures and 0 successes completely determined.

{com}. 
. 
. 
. *** TABLE 2
. * Model 4
. logit onset_use lag_ln_dist2cic lag_ln_dist2cinc intbnd dia_sec peton_use pop_use_ln ethdiff ///
>   peaceyrs _spline* rdrgas, robust cl(gwno)

{txt}Iteration 0:   log pseudolikelihood = {res}-684.30126
{txt}Iteration 1:   log pseudolikelihood = {res}-666.63327
{txt}Iteration 2:   log pseudolikelihood = {res}-626.93626
{txt}Iteration 3:   log pseudolikelihood = {res}-624.26718
{txt}Iteration 4:   log pseudolikelihood = {res}-624.20838
{txt}Iteration 5:   log pseudolikelihood = {res}-624.20834

{txt}Logistic regression                               Number of obs   = {res}      6208
                                                  {txt}Wald chi2({res}12{txt})   = {res}    104.40
                                                  {txt}Prob > chi2     = {res}    0.0000
{txt}Log pseudolikelihood = {res}-624.20834                 {txt}Pseudo R2       = {res}    0.0878

                                  {txt}(Std. Err. adjusted for {res}22{txt} clusters in gwno)
{hline 13}{c TT}{hline 64}
             {c |}               Robust
   onset_use {c |}      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
{hline 13}{c +}{hline 64}
lag_ln_di~ic {c |}  {res} .0120313   .0629979     0.19   0.849    -.1114424    .1355049
{txt}lag_ln_di~nc {c |}  {res}-.0734772    .039912    -1.84   0.066    -.1517033    .0047488
      {txt}intbnd {c |}  {res}-.2432062   .3326262    -0.73   0.465    -.8951415    .4087292
     {txt}dia_sec {c |}  {res} .7619319    .272702     2.79   0.005     .2274458    1.296418
   {txt}peton_use {c |}  {res} .6909645   .4464118     1.55   0.122    -.1839865    1.565915
  {txt}pop_use_ln {c |}  {res}-.0033814   .1574973    -0.02   0.983    -.3120704    .3053076
     {txt}ethdiff {c |}  {res} .0215502   .3740578     0.06   0.954    -.7115896    .7546899
    {txt}peaceyrs {c |}  {res} .1636187   .1676327     0.98   0.329    -.1649354    .4921727
    {txt}_spline1 {c |}  {res} .0048593   .0028326     1.72   0.086    -.0006926    .0104111
    {txt}_spline2 {c |}  {res} -.002691   .0024722    -1.09   0.276    -.0075364    .0021544
    {txt}_spline3 {c |}  {res} .0001441    .001463     0.10   0.922    -.0027234    .0030116
      {txt}rdrgas {c |}  {res} .3332422   .3130906     1.06   0.287     -.280404    .9468884
       {txt}_cons {c |}  {res}-2.543829   2.355678    -1.08   0.280    -7.160873    2.073214
{txt}{hline 13}{c BT}{hline 64}

{com}. 
. * Model 5
. logit onset_use lag_ln_dist2cic lag_ln_dist2cinc intbnd dia_sec peton_use pop_use_ln ethdiff ///
>   peaceyrs _spline* rdrged, robust cl(gwno) 

{txt}Iteration 0:   log pseudolikelihood = {res}-684.30126
{txt}Iteration 1:   log pseudolikelihood = {res}-664.88682
{txt}Iteration 2:   log pseudolikelihood = {res}-627.57518
{txt}Iteration 3:   log pseudolikelihood = {res}-624.99578
{txt}Iteration 4:   log pseudolikelihood = {res} -624.9366
{txt}Iteration 5:   log pseudolikelihood = {res}-624.93655

{txt}Logistic regression                               Number of obs   = {res}      6208
                                                  {txt}Wald chi2({res}12{txt})   = {res}    158.53
                                                  {txt}Prob > chi2     = {res}    0.0000
{txt}Log pseudolikelihood = {res}-624.93655                 {txt}Pseudo R2       = {res}    0.0868

                                  {txt}(Std. Err. adjusted for {res}22{txt} clusters in gwno)
{hline 13}{c TT}{hline 64}
             {c |}               Robust
   onset_use {c |}      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
{hline 13}{c +}{hline 64}
lag_ln_di~ic {c |}  {res} .0103571   .0629326     0.16   0.869    -.1129885    .1337027
{txt}lag_ln_di~nc {c |}  {res} -.078189   .0381058    -2.05   0.040    -.1528749   -.0035031
      {txt}intbnd {c |}  {res}-.2199656   .3469848    -0.63   0.526    -.9000434    .4601122
     {txt}dia_sec {c |}  {res} .7551659    .280378     2.69   0.007     .2056351    1.304697
   {txt}peton_use {c |}  {res}  .689616   .4639154     1.49   0.137    -.2196415    1.598873
  {txt}pop_use_ln {c |}  {res} .0053027   .1616603     0.03   0.974    -.3115457    .3221511
     {txt}ethdiff {c |}  {res} .0403128   .3616508     0.11   0.911    -.6685098    .7491353
    {txt}peaceyrs {c |}  {res} .1671985   .1684406     0.99   0.321    -.1629391    .4973361
    {txt}_spline1 {c |}  {res} .0049847   .0028532     1.75   0.081    -.0006075    .0105768
    {txt}_spline2 {c |}  {res}-.0027968   .0024868    -1.12   0.261    -.0076708    .0020773
    {txt}_spline3 {c |}  {res} .0001922   .0014688     0.13   0.896    -.0026867     .003071
      {txt}rdrged {c |}  {res} .1170461   .1507277     0.78   0.437    -.1783747    .4124669
       {txt}_cons {c |}  {res}-2.574775   2.385387    -1.08   0.280    -7.250048    2.100499
{txt}{hline 13}{c BT}{hline 64}

{com}. 
. * Model 6
. logit onset_use lag_ln_dist2cic lag_ln_dist2cinc intbnd dia_sec peton_use pop_use_ln ethdiff ///
>   peaceyrs _spline* rdrgas_c rdrgas2_c, robust cl(gwno) 

{txt}Iteration 0:   log pseudolikelihood = {res}-684.30126
{txt}Iteration 1:   log pseudolikelihood = {res} -666.4915
{txt}Iteration 2:   log pseudolikelihood = {res}-625.25401
{txt}Iteration 3:   log pseudolikelihood = {res}-622.58163
{txt}Iteration 4:   log pseudolikelihood = {res}-622.52655
{txt}Iteration 5:   log pseudolikelihood = {res}-622.52652

{txt}Logistic regression                               Number of obs   = {res}      6208
                                                  {txt}Wald chi2({res}13{txt})   = {res}    145.25
                                                  {txt}Prob > chi2     = {res}    0.0000
{txt}Log pseudolikelihood = {res}-622.52652                 {txt}Pseudo R2       = {res}    0.0903

                                  {txt}(Std. Err. adjusted for {res}22{txt} clusters in gwno)
{hline 13}{c TT}{hline 64}
             {c |}               Robust
   onset_use {c |}      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
{hline 13}{c +}{hline 64}
lag_ln_di~ic {c |}  {res} .0127374   .0632055     0.20   0.840    -.1111432    .1366179
{txt}lag_ln_di~nc {c |}  {res} -.073395   .0400645    -1.83   0.067    -.1519199    .0051299
      {txt}intbnd {c |}  {res}-.2321864   .3381892    -0.69   0.492    -.8950252    .4306523
     {txt}dia_sec {c |}  {res} .8178046     .26729     3.06   0.002     .2939257    1.341683
   {txt}peton_use {c |}  {res} .7076349   .4503469     1.57   0.116    -.1750288    1.590299
  {txt}pop_use_ln {c |}  {res}-.0022486   .1531571    -0.01   0.988    -.3024311    .2979339
     {txt}ethdiff {c |}  {res}  .026031   .3818873     0.07   0.946    -.7224544    .7745164
    {txt}peaceyrs {c |}  {res} .1580658   .1688458     0.94   0.349    -.1728659    .4889975
    {txt}_spline1 {c |}  {res}  .004727   .0028426     1.66   0.096    -.0008445    .0102985
    {txt}_spline2 {c |}  {res}-.0025929   .0024805    -1.05   0.296    -.0074546    .0022688
    {txt}_spline3 {c |}  {res} .0001058   .0014678     0.07   0.943     -.002771    .0029826
    {txt}rdrgas_c {c |}  {res} .1496555   .3022859     0.50   0.621     -.442814     .742125
   {txt}rdrgas2_c {c |}  {res} .4644687   .1384236     3.36   0.001     .1931634     .735774
       {txt}_cons {c |}  {res}-2.619014   2.332779    -1.12   0.262    -7.191176    1.953149
{txt}{hline 13}{c BT}{hline 64}

{com}. 
. * Model 7
. logit onset_use lag_ln_dist2cic lag_ln_dist2cinc intbnd dia_sec peton_use pop_use_ln ethdiff ///
>   peaceyrs _spline* rdrged_c rdrged2_c, robust cl(gwno) 

{txt}Iteration 0:   log pseudolikelihood = {res}-684.30126
{txt}Iteration 1:   log pseudolikelihood = {res}-665.44637
{txt}Iteration 2:   log pseudolikelihood = {res}-627.55063
{txt}Iteration 3:   log pseudolikelihood = {res}-624.93967
{txt}Iteration 4:   log pseudolikelihood = {res}-624.87977
{txt}Iteration 5:   log pseudolikelihood = {res}-624.87972

{txt}Logistic regression                               Number of obs   = {res}      6208
                                                  {txt}Wald chi2({res}13{txt})   = {res}    182.41
                                                  {txt}Prob > chi2     = {res}    0.0000
{txt}Log pseudolikelihood = {res}-624.87972                 {txt}Pseudo R2       = {res}    0.0868

                                  {txt}(Std. Err. adjusted for {res}22{txt} clusters in gwno)
{hline 13}{c TT}{hline 64}
             {c |}               Robust
   onset_use {c |}      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
{hline 13}{c +}{hline 64}
lag_ln_di~ic {c |}  {res} .0106542   .0629915     0.17   0.866    -.1128069    .1341154
{txt}lag_ln_di~nc {c |}  {res}-.0777631    .038321    -2.03   0.042    -.1528709   -.0026554
      {txt}intbnd {c |}  {res}-.2245951   .3433031    -0.65   0.513    -.8974568    .4482667
     {txt}dia_sec {c |}  {res}  .754157   .2779747     2.71   0.007     .2093366    1.298977
   {txt}peton_use {c |}  {res} .6991615   .4602191     1.52   0.129    -.2028514    1.601174
  {txt}pop_use_ln {c |}  {res}  .005817   .1610216     0.04   0.971    -.3097795    .3214135
     {txt}ethdiff {c |}  {res} .0308285   .3709845     0.08   0.934    -.6962879    .7579449
    {txt}peaceyrs {c |}  {res} .1676982   .1673065     1.00   0.316    -.1602165    .4956128
    {txt}_spline1 {c |}  {res} .0049814   .0028493     1.75   0.080     -.000603    .0105658
    {txt}_spline2 {c |}  {res}-.0027879   .0024908    -1.12   0.263    -.0076697     .002094
    {txt}_spline3 {c |}  {res}  .000185   .0014751     0.13   0.900    -.0027063    .0030762
    {txt}rdrged_c {c |}  {res} .1558602   .2123234     0.73   0.463    -.2602861    .5720065
   {txt}rdrged2_c {c |}  {res}-.0225797   .0472303    -0.48   0.633    -.1151494    .0699899
       {txt}_cons {c |}  {res}-2.520308   2.380129    -1.06   0.290    -7.185274    2.144659
{txt}{hline 13}{c BT}{hline 64}

{com}.  
. 
. 
. *** TABLE 3
. * Model 8
. logit onset_use lag_ln_dist2cic lag_ln_dist2cinc intbnd dia_sec peton_use pop_use_ln ethdiff ///
>   peaceyrs _spline* asset_gini, robust cl(gwno) 

{txt}Iteration 0:   log pseudolikelihood = {res}-684.30126
{txt}Iteration 1:   log pseudolikelihood = {res}-670.70206
{txt}Iteration 2:   log pseudolikelihood = {res}-615.10043
{txt}Iteration 3:   log pseudolikelihood = {res}-611.68684
{txt}Iteration 4:   log pseudolikelihood = {res}-611.61354
{txt}Iteration 5:   log pseudolikelihood = {res}-611.61348

{txt}Logistic regression                               Number of obs   = {res}      6208
                                                  {txt}Wald chi2({res}12{txt})   = {res}    141.43
                                                  {txt}Prob > chi2     = {res}    0.0000
{txt}Log pseudolikelihood = {res}-611.61348                 {txt}Pseudo R2       = {res}    0.1062

                                  {txt}(Std. Err. adjusted for {res}22{txt} clusters in gwno)
{hline 13}{c TT}{hline 64}
             {c |}               Robust
   onset_use {c |}      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
{hline 13}{c +}{hline 64}
lag_ln_di~ic {c |}  {res} .0159879   .0631608     0.25   0.800     -.107805    .1397807
{txt}lag_ln_di~nc {c |}  {res} -.055155   .0415838    -1.33   0.185    -.1366577    .0263477
      {txt}intbnd {c |}  {res}-.4223967   .3308435    -1.28   0.202    -1.070838    .2260446
     {txt}dia_sec {c |}  {res}  .657954   .2513738     2.62   0.009     .1652704    1.150638
   {txt}peton_use {c |}  {res}  .553809   .3626198     1.53   0.127    -.1569127    1.264531
  {txt}pop_use_ln {c |}  {res}-.0609657   .1347825    -0.45   0.651    -.3251345     .203203
     {txt}ethdiff {c |}  {res} .0985039   .3903289     0.25   0.801    -.6665267    .8635346
    {txt}peaceyrs {c |}  {res} .1853133    .170477     1.09   0.277    -.1488156    .5194421
    {txt}_spline1 {c |}  {res} .0046897   .0029726     1.58   0.115    -.0011364    .0105158
    {txt}_spline2 {c |}  {res}-.0024332   .0025594    -0.95   0.342    -.0074496    .0025832
    {txt}_spline3 {c |}  {res}-.0000151   .0014817    -0.01   0.992    -.0029193    .0028891
  {txt}asset_gini {c |}  {res}   3.4911   1.029972     3.39   0.001     1.472393    5.509807
       {txt}_cons {c |}  {res}-3.938695   2.400109    -1.64   0.101    -8.642822    .7654327
{txt}{hline 13}{c BT}{hline 64}

{com}. 
. * Model 9
. logit onset_use lag_ln_dist2cic lag_ln_dist2cinc intbnd dia_sec peton_use pop_use_ln ethdiff ///
>   peaceyrs _spline* education_gini, robust cl(gwno) 

{txt}Iteration 0:   log pseudolikelihood = {res}-684.30126
{txt}Iteration 1:   log pseudolikelihood = {res}-666.77032
{txt}Iteration 2:   log pseudolikelihood = {res}-596.73376
{txt}Iteration 3:   log pseudolikelihood = {res}-591.67536
{txt}Iteration 4:   log pseudolikelihood = {res}-591.51643
{txt}Iteration 5:   log pseudolikelihood = {res}-591.51619

{txt}Logistic regression                               Number of obs   = {res}      6208
                                                  {txt}Wald chi2({res}12{txt})   = {res}    225.97
                                                  {txt}Prob > chi2     = {res}    0.0000
{txt}Log pseudolikelihood = {res}-591.51619                 {txt}Pseudo R2       = {res}    0.1356

                                  {txt}(Std. Err. adjusted for {res}22{txt} clusters in gwno)
{hline 13}{c TT}{hline 64}
             {c |}               Robust
   onset_use {c |}      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
{hline 13}{c +}{hline 64}
lag_ln_di~ic {c |}  {res} .0237935   .0526557     0.45   0.651    -.0794097    .1269968
{txt}lag_ln_di~nc {c |}  {res}-.0768746   .0378793    -2.03   0.042    -.1511166   -.0026326
      {txt}intbnd {c |}  {res}-.4847564   .3341079    -1.45   0.147    -1.139596    .1700831
     {txt}dia_sec {c |}  {res} .6520504   .2476047     2.63   0.008     .1667541    1.137347
   {txt}peton_use {c |}  {res} .7682613   .2892879     2.66   0.008     .2012675    1.335255
  {txt}pop_use_ln {c |}  {res} .0173551   .1389915     0.12   0.901    -.2550631    .2897734
     {txt}ethdiff {c |}  {res} .0142189   .3858792     0.04   0.971    -.7420905    .7705282
    {txt}peaceyrs {c |}  {res} .3060989   .1473708     2.08   0.038     .0172575    .5949403
    {txt}_spline1 {c |}  {res} .0058796   .0026311     2.23   0.025     .0007227    .0110364
    {txt}_spline2 {c |}  {res}-.0025157   .0022763    -1.11   0.269    -.0069771    .0019458
    {txt}_spline3 {c |}  {res}-.0004627   .0013499    -0.34   0.732    -.0031085    .0021831
{txt}education_~i {c |}  {res} 3.600173   .8804885     4.09   0.000     1.874447    5.325898
       {txt}_cons {c |}  {res}-5.617969   2.211062    -2.54   0.011    -9.951571   -1.284366
{txt}{hline 13}{c BT}{hline 64}
Note: 3 failures and 0 successes completely determined.

{com}. 
. * Model 10
. logit onset_use lag_ln_dist2cic lag_ln_dist2cinc intbnd dia_sec peton_use pop_use_ln ethdiff ///
>   peaceyrs _spline* elf_reg, robust cl(gwno)

{txt}Iteration 0:   log pseudolikelihood = {res}-682.05425
{txt}Iteration 1:   log pseudolikelihood = {res}-659.01543
{txt}Iteration 2:   log pseudolikelihood = {res}-625.65246
{txt}Iteration 3:   log pseudolikelihood = {res}-623.30853
{txt}Iteration 4:   log pseudolikelihood = {res}-623.25319
{txt}Iteration 5:   log pseudolikelihood = {res}-623.25315

{txt}Logistic regression                               Number of obs   = {res}      6113
                                                  {txt}Wald chi2({res}12{txt})   = {res}     68.64
                                                  {txt}Prob > chi2     = {res}    0.0000
{txt}Log pseudolikelihood = {res}-623.25315                 {txt}Pseudo R2       = {res}    0.0862

                                  {txt}(Std. Err. adjusted for {res}22{txt} clusters in gwno)
{hline 13}{c TT}{hline 64}
             {c |}               Robust
   onset_use {c |}      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
{hline 13}{c +}{hline 64}
lag_ln_di~ic {c |}  {res} .0092585   .0624324     0.15   0.882    -.1131067    .1316237
{txt}lag_ln_di~nc {c |}  {res}-.0797657   .0374461    -2.13   0.033    -.1531587   -.0063726
      {txt}intbnd {c |}  {res}-.2686061   .3455865    -0.78   0.437    -.9459432    .4087309
     {txt}dia_sec {c |}  {res} .7400693   .2737441     2.70   0.007     .2035408    1.276598
   {txt}peton_use {c |}  {res} .7082007   .5389756     1.31   0.189     -.348172    1.764573
  {txt}pop_use_ln {c |}  {res}-.0039027   .1645009    -0.02   0.981    -.3263185     .318513
     {txt}ethdiff {c |}  {res} .0139832   .3638387     0.04   0.969    -.6991277     .727094
    {txt}peaceyrs {c |}  {res} .1629531   .1703108     0.96   0.339    -.1708499    .4967562
    {txt}_spline1 {c |}  {res} .0049433   .0028698     1.72   0.085    -.0006813     .010568
    {txt}_spline2 {c |}  {res} -.002809   .0025177    -1.12   0.265    -.0077436    .0021256
    {txt}_spline3 {c |}  {res} .0002218    .001491     0.15   0.882    -.0027006    .0031442
     {txt}elf_reg {c |}  {res} .5774095   .5656196     1.02   0.307    -.5311845    1.686003
       {txt}_cons {c |}  {res}-2.559122   2.382328    -1.07   0.283    -7.228399    2.110155
{txt}{hline 13}{c BT}{hline 64}

{com}. 
. * Model 11
. logit onset_use lag_ln_dist2cic lag_ln_dist2cinc intbnd dia_sec peton_use pop_use_ln ethdiff ///
>   peaceyrs _spline* education_gini asset_gini elf_reg, robust cl(gwno) 

{txt}Iteration 0:   log pseudolikelihood = {res}-682.05425
{txt}Iteration 1:   log pseudolikelihood = {res}-681.85263
{txt}Iteration 2:   log pseudolikelihood = {res}-591.16532
{txt}Iteration 3:   log pseudolikelihood = {res}-585.91031
{txt}Iteration 4:   log pseudolikelihood = {res}-585.75342
{txt}Iteration 5:   log pseudolikelihood = {res}-585.75318

{txt}Logistic regression                               Number of obs   = {res}      6113
                                                  {txt}Wald chi2({res}14{txt})   = {res}    310.57
                                                  {txt}Prob > chi2     = {res}    0.0000
{txt}Log pseudolikelihood = {res}-585.75318                 {txt}Pseudo R2       = {res}    0.1412

                                  {txt}(Std. Err. adjusted for {res}22{txt} clusters in gwno)
{hline 13}{c TT}{hline 64}
             {c |}               Robust
   onset_use {c |}      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
{hline 13}{c +}{hline 64}
lag_ln_di~ic {c |}  {res} .0248254   .0544531     0.46   0.648    -.0819007    .1315516
{txt}lag_ln_di~nc {c |}  {res}-.0655511   .0401035    -1.63   0.102    -.1441524    .0130503
      {txt}intbnd {c |}  {res}-.6427065    .291407    -2.21   0.027    -1.213854   -.0715594
     {txt}dia_sec {c |}  {res} .6185538    .220092     2.81   0.005     .1871815    1.049926
   {txt}peton_use {c |}  {res} .7362733    .321167     2.29   0.022     .1067976    1.365749
  {txt}pop_use_ln {c |}  {res}-.0284654   .1250421    -0.23   0.820    -.2735433    .2166126
     {txt}ethdiff {c |}  {res}-.0719022   .4155381    -0.17   0.863     -.886342    .7425376
    {txt}peaceyrs {c |}  {res} .3062975   .1522553     2.01   0.044     .0078826    .6047124
    {txt}_spline1 {c |}  {res} .0055538   .0028083     1.98   0.048     .0000497     .011058
    {txt}_spline2 {c |}  {res}-.0022757   .0024002    -0.95   0.343    -.0069801    .0024286
    {txt}_spline3 {c |}  {res}-.0005391   .0013922    -0.39   0.699    -.0032678    .0021896
{txt}education_~i {c |}  {res} 3.254325   .8629179     3.77   0.000     1.563037    4.945613
  {txt}asset_gini {c |}  {res} 1.921877   .9686107     1.98   0.047     .0234352    3.820319
     {txt}elf_reg {c |}  {res} .7057005   .5888411     1.20   0.231    -.4484069    1.859808
       {txt}_cons {c |}  {res}-6.188125   2.175752    -2.84   0.004    -10.45252   -1.923729
{txt}{hline 13}{c BT}{hline 64}

{com}. 
. 
. 
. *** TABLE 4
. * Model 12
. logit onset_use lag_ln_dist2cic lag_ln_dist2cinc intbnd pop_use_ln ethdiff ///
>   peaceyrs _spline* dia_sec rdrgas_c rdrgas_dia, robust cl(gwno)

{txt}Iteration 0:   log pseudolikelihood = {res}-684.30126
{txt}Iteration 1:   log pseudolikelihood = {res} -671.4449
{txt}Iteration 2:   log pseudolikelihood = {res}-629.11894
{txt}Iteration 3:   log pseudolikelihood = {res}-626.65966
{txt}Iteration 4:   log pseudolikelihood = {res}-626.61121
{txt}Iteration 5:   log pseudolikelihood = {res}-626.61117

{txt}Logistic regression                               Number of obs   = {res}      6208
                                                  {txt}Wald chi2({res}12{txt})   = {res}     97.87
                                                  {txt}Prob > chi2     = {res}    0.0000
{txt}Log pseudolikelihood = {res}-626.61117                 {txt}Pseudo R2       = {res}    0.0843

                                  {txt}(Std. Err. adjusted for {res}22{txt} clusters in gwno)
{hline 13}{c TT}{hline 64}
             {c |}               Robust
   onset_use {c |}      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
{hline 13}{c +}{hline 64}
lag_ln_di~ic {c |}  {res} .0130372   .0644546     0.20   0.840    -.1132915    .1393659
{txt}lag_ln_di~nc {c |}  {res}-.0710324   .0413578    -1.72   0.086    -.1520922    .0100273
      {txt}intbnd {c |}  {res} -.267299   .3320995    -0.80   0.421    -.9182021    .3836041
  {txt}pop_use_ln {c |}  {res} .0233792   .1585801     0.15   0.883     -.287432    .3341904
     {txt}ethdiff {c |}  {res} .0078821   .3783901     0.02   0.983    -.7337489    .7495131
    {txt}peaceyrs {c |}  {res} .1428751   .1722975     0.83   0.407    -.1948219    .4805721
    {txt}_spline1 {c |}  {res} .0047101    .002783     1.69   0.091    -.0007444    .0101646
    {txt}_spline2 {c |}  {res}-.0026809   .0024592    -1.09   0.276    -.0075008    .0021391
    {txt}_spline3 {c |}  {res} .0001941   .0014734     0.13   0.895    -.0026937    .0030819
     {txt}dia_sec {c |}  {res} .6750328   .2540248     2.66   0.008     .1771534    1.172912
    {txt}rdrgas_c {c |}  {res} .3115396   .3282388     0.95   0.343    -.3317966    .9548759
  {txt}rdrgas_dia {c |}  {res} .5388029   .5206761     1.03   0.301    -.4817036    1.559309
       {txt}_cons {c |}  {res}-2.670204   2.340014    -1.14   0.254    -7.256548     1.91614
{txt}{hline 13}{c BT}{hline 64}

{com}. 
. * Model 13
. logit onset_use lag_ln_dist2cic lag_ln_dist2cinc intbnd pop_use_ln ethdiff ///
>   peaceyrs _spline* peton_use  rdrgas_c rdrgas_pet, robust cl(gwno)

{txt}Iteration 0:   log pseudolikelihood = {res}-684.30126
{txt}Iteration 1:   log pseudolikelihood = {res}-681.41124
{txt}Iteration 2:   log pseudolikelihood = {res}-631.23169
{txt}Iteration 3:   log pseudolikelihood = {res}-628.76701
{txt}Iteration 4:   log pseudolikelihood = {res}-628.70872
{txt}Iteration 5:   log pseudolikelihood = {res}-628.70867

{txt}Logistic regression                               Number of obs   = {res}      6208
                                                  {txt}Wald chi2({res}12{txt})   = {res}    185.99
                                                  {txt}Prob > chi2     = {res}    0.0000
{txt}Log pseudolikelihood = {res}-628.70867                 {txt}Pseudo R2       = {res}    0.0812

                                  {txt}(Std. Err. adjusted for {res}22{txt} clusters in gwno)
{hline 13}{c TT}{hline 64}
             {c |}               Robust
   onset_use {c |}      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
{hline 13}{c +}{hline 64}
lag_ln_di~ic {c |}  {res} .0135243   .0664331     0.20   0.839    -.1166821    .1437307
{txt}lag_ln_di~nc {c |}  {res}-.0806982   .0433228    -1.86   0.063    -.1656095     .004213
      {txt}intbnd {c |}  {res}-.2714488   .3309706    -0.82   0.412    -.9201392    .3772416
  {txt}pop_use_ln {c |}  {res} .0054415   .1581396     0.03   0.973    -.3045065    .3153895
     {txt}ethdiff {c |}  {res} .0400094   .3746919     0.11   0.915    -.6943732     .774392
    {txt}peaceyrs {c |}  {res} .1435857   .1704979     0.84   0.400    -.1905841    .4777555
    {txt}_spline1 {c |}  {res} .0046896   .0027901     1.68   0.093    -.0007788     .010158
    {txt}_spline2 {c |}  {res}  -.00271    .002465    -1.10   0.272    -.0075413    .0021213
    {txt}_spline3 {c |}  {res}   .00024   .0014798     0.16   0.871    -.0026603    .0031403
   {txt}peton_use {c |}  {res} .5422891   .4016922     1.35   0.177     -.245013    1.329591
    {txt}rdrgas_c {c |}  {res} .2581527   .3145102     0.82   0.412    -.3582759    .8745813
  {txt}rdrgas_pet {c |}  {res} .9768456    .812527     1.20   0.229    -.6156782    2.569369
       {txt}_cons {c |}  {res}-2.355379   2.408886    -0.98   0.328    -7.076708     2.36595
{txt}{hline 13}{c BT}{hline 64}

{com}. 
. * Model 14
. logit onset_use lag_ln_dist2cic lag_ln_dist2cinc intbnd pop_use_ln ethdiff ///
>   peaceyrs _spline* nr_c  rdrgas_c rdrgas_nr, robust cl(gwno) 

{txt}Iteration 0:   log pseudolikelihood = {res}-684.30126
{txt}Iteration 1:   log pseudolikelihood = {res}-677.92146
{txt}Iteration 2:   log pseudolikelihood = {res}-625.69096
{txt}Iteration 3:   log pseudolikelihood = {res}-622.98955
{txt}Iteration 4:   log pseudolikelihood = {res}-622.93493
{txt}Iteration 5:   log pseudolikelihood = {res}-622.93489

{txt}Logistic regression                               Number of obs   = {res}      6208
                                                  {txt}Wald chi2({res}12{txt})   = {res}     97.63
                                                  {txt}Prob > chi2     = {res}    0.0000
{txt}Log pseudolikelihood = {res}-622.93489                 {txt}Pseudo R2       = {res}    0.0897

                                  {txt}(Std. Err. adjusted for {res}22{txt} clusters in gwno)
{hline 13}{c TT}{hline 64}
             {c |}               Robust
   onset_use {c |}      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
{hline 13}{c +}{hline 64}
lag_ln_di~ic {c |}  {res}  .010056   .0644984     0.16   0.876    -.1163585    .1364705
{txt}lag_ln_di~nc {c |}  {res}-.0762816    .039865    -1.91   0.056    -.1544155    .0018524
      {txt}intbnd {c |}  {res}-.2442167   .3396591    -0.72   0.472    -.9099363    .4215029
  {txt}pop_use_ln {c |}  {res} .0094595   .1658812     0.06   0.955    -.3156616    .3345807
     {txt}ethdiff {c |}  {res}-.0019938   .3848201    -0.01   0.996    -.7562273    .7522397
    {txt}peaceyrs {c |}  {res} .1841937   .1733298     1.06   0.288    -.1555265    .5239138
    {txt}_spline1 {c |}  {res}   .00513   .0029075     1.76   0.078    -.0005686    .0108286
    {txt}_spline2 {c |}  {res}-.0028519    .002513    -1.13   0.256    -.0077773    .0020735
    {txt}_spline3 {c |}  {res} .0001885   .0014695     0.13   0.898    -.0026917    .0030688
        {txt}nr_c {c |}  {res} .7037128    .303111     2.32   0.020     .1096261      1.2978
    {txt}rdrgas_c {c |}  {res} .3102167   .2766121     1.12   0.262    -.2319331    .8523664
   {txt}rdrgas_nr {c |}  {res} .8439407    .362065     2.33   0.020     .1343063    1.553575
       {txt}_cons {c |}  {res}-2.486663   2.435864    -1.02   0.307    -7.260868    2.287542
{txt}{hline 13}{c BT}{hline 64}

{com}. 
. 
. 
. *** FIGURE 2
. capture drop b1-b13
{txt}
{com}. capture drop b14
{txt}
{com}. capture drop plo phi
{txt}
{com}. capture drop pavg
{txt}
{com}. capture drop ageaxis
{txt}
{com}. capture drop pi
{txt}
{com}. estsimp logit onset_use lag_ln_dist2cic lag_ln_dist2cinc intbnd dia_sec peton_use pop_use_ln ethdiff ///
> peaceyrs _spline* rdrgas_c rdrgas2_c, robust cl(gwno)

{txt}Iteration 0:   log pseudolikelihood = {res}-684.30126
{txt}Iteration 1:   log pseudolikelihood = {res} -666.4915
{txt}Iteration 2:   log pseudolikelihood = {res}-625.25401
{txt}Iteration 3:   log pseudolikelihood = {res}-622.58163
{txt}Iteration 4:   log pseudolikelihood = {res}-622.52655
{txt}Iteration 5:   log pseudolikelihood = {res}-622.52652

{txt}Logistic regression                               Number of obs   = {res}      6208
                                                  {txt}Wald chi2({res}13{txt})   = {res}    145.25
                                                  {txt}Prob > chi2     = {res}    0.0000
{txt}Log pseudolikelihood = {res}-622.52652                 {txt}Pseudo R2       = {res}    0.0903

                                  {txt}(Std. Err. adjusted for {res}22{txt} clusters in gwno)
{hline 13}{c TT}{hline 64}
             {c |}               Robust
   onset_use {c |}      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
{hline 13}{c +}{hline 64}
lag_ln_di~ic {c |}  {res} .0127374   .0632055     0.20   0.840    -.1111432    .1366179
{txt}lag_ln_di~nc {c |}  {res} -.073395   .0400645    -1.83   0.067    -.1519199    .0051299
      {txt}intbnd {c |}  {res}-.2321864   .3381892    -0.69   0.492    -.8950252    .4306523
     {txt}dia_sec {c |}  {res} .8178046     .26729     3.06   0.002     .2939257    1.341683
   {txt}peton_use {c |}  {res} .7076349   .4503469     1.57   0.116    -.1750288    1.590299
  {txt}pop_use_ln {c |}  {res}-.0022486   .1531571    -0.01   0.988    -.3024311    .2979339
     {txt}ethdiff {c |}  {res}  .026031   .3818873     0.07   0.946    -.7224544    .7745164
    {txt}peaceyrs {c |}  {res} .1580658   .1688458     0.94   0.349    -.1728659    .4889975
    {txt}_spline1 {c |}  {res}  .004727   .0028426     1.66   0.096    -.0008445    .0102985
    {txt}_spline2 {c |}  {res}-.0025929   .0024805    -1.05   0.296    -.0074546    .0022688
    {txt}_spline3 {c |}  {res} .0001058   .0014678     0.07   0.943     -.002771    .0029826
    {txt}rdrgas_c {c |}  {res} .1496555   .3022859     0.50   0.621     -.442814     .742125
   {txt}rdrgas2_c {c |}  {res} .4644687   .1384236     3.36   0.001     .1931634     .735774
       {txt}_cons {c |}  {res}-2.619014   2.332779    -1.12   0.262    -7.191176    1.953149
{txt}{hline 13}{c BT}{hline 64}

{res}Simulating main parameters.  Please wait....
% of simulations completed: 7% 14% 21% 28% 35% 42% 50% 57% 64% 71% 78% 85% 92% 100% 

Number of simulations  : 1000
Names of new variables : b1 b2 b3 b4 b5 b6 b7 b8 b9 b10 b11 b12 b13 b14
{txt}
{com}. generate plo = .
{txt}(6626 missing values generated)

{com}. generate pavg = .
{txt}(6626 missing values generated)

{com}. generate phi = .
{txt}(6626 missing values generated)

{com}. generate ageaxis = _n - 9 in 1/28
{txt}(6598 missing values generated)

{com}. setx mean
{txt}
{com}. local a = -8
{txt}
{com}. while `a' <= 19 {c -(}
{txt}  2{com}.         local b = (`a' - 2)/10
{txt}  3{com}.         local b_sq = `b'^2
{txt}  4{com}.         setx rdrgas_c `b' rdrgas2_c `b_sq'
{txt}  5{com}.         simqi, prval(1) genpr(pi)
{txt}  6{com}.         _pctile pi, p(10,50,90)
{txt}  7{com}.         replace plo = r(r1) if ageaxis==`a'
{txt}  8{com}.         replace pavg = r(r2) if ageaxis==`a'
{txt}  9{com}.         replace phi = r(r3) if ageaxis==`a'
{txt} 10{com}.         drop pi
{txt} 11{com}.         local a = `a' + 1
{txt} 12{com}. {c )-}

{txt}      Quantity of Interest |     Mean       Std. Err.    [95% Conf. Interval]
---------------------------+--------------------------------------------------
            Pr(onset_~e=1) |  {res} .0087499     .0046559     .0030574    .0201398

Simqi generated the following new variable(s): pi
{txt}(1 real change made)
(1 real change made)
(1 real change made)

      Quantity of Interest |     Mean       Std. Err.    [95% Conf. Interval]
---------------------------+--------------------------------------------------
            Pr(onset_~e=1) |  {res} .0095782      .004779     .0035231    .0216215

Simqi generated the following new variable(s): pi
{txt}(1 real change made)
(1 real change made)
(1 real change made)

      Quantity of Interest |     Mean       Std. Err.    [95% Conf. Interval]
---------------------------+--------------------------------------------------
            Pr(onset_~e=1) |  {res}  .010398     .0048621     .0040699    .0225668

Simqi generated the following new variable(s): pi
{txt}(1 real change made)
(1 real change made)
(1 real change made)

      Quantity of Interest |     Mean       Std. Err.    [95% Conf. Interval]
---------------------------+--------------------------------------------------
            Pr(onset_~e=1) |  {res} .0111935     .0049016     .0046189    .0236762

Simqi generated the following new variable(s): pi
{txt}(1 real change made)
(1 real change made)
(1 real change made)

      Quantity of Interest |     Mean       Std. Err.    [95% Conf. Interval]
---------------------------+--------------------------------------------------
            Pr(onset_~e=1) |  {res} .0119484     .0048951     .0052115     .024255

Simqi generated the following new variable(s): pi
{txt}(1 real change made)
(1 real change made)
(1 real change made)

      Quantity of Interest |     Mean       Std. Err.    [95% Conf. Interval]
---------------------------+--------------------------------------------------
            Pr(onset_~e=1) |  {res} .0126463     .0048425     .0058425    .0246121

Simqi generated the following new variable(s): pi
{txt}(1 real change made)
(1 real change made)
(1 real change made)

      Quantity of Interest |     Mean       Std. Err.    [95% Conf. Interval]
---------------------------+--------------------------------------------------
            Pr(onset_~e=1) |  {res} .0132716     .0047458     .0065017    .0247043

Simqi generated the following new variable(s): pi
{txt}(1 real change made)
(1 real change made)
(1 real change made)

      Quantity of Interest |     Mean       Std. Err.    [95% Conf. Interval]
---------------------------+--------------------------------------------------
            Pr(onset_~e=1) |  {res} .0138098     .0046101     .0071035    .0247149

Simqi generated the following new variable(s): pi
{txt}(1 real change made)
(1 real change made)
(1 real change made)

      Quantity of Interest |     Mean       Std. Err.    [95% Conf. Interval]
---------------------------+--------------------------------------------------
            Pr(onset_~e=1) |  {res} .0142484     .0044434     .0076394    .0247346

Simqi generated the following new variable(s): pi
{txt}(1 real change made)
(1 real change made)
(1 real change made)

      Quantity of Interest |     Mean       Std. Err.    [95% Conf. Interval]
---------------------------+--------------------------------------------------
            Pr(onset_~e=1) |  {res} .0145775     .0042572     .0081222    .0248116

Simqi generated the following new variable(s): pi
{txt}(1 real change made)
(1 real change made)
(1 real change made)

      Quantity of Interest |     Mean       Std. Err.    [95% Conf. Interval]
---------------------------+--------------------------------------------------
            Pr(onset_~e=1) |  {res} .0147898     .0040664     .0085888    .0246672

Simqi generated the following new variable(s): pi
{txt}(1 real change made)
(1 real change made)
(1 real change made)

      Quantity of Interest |     Mean       Std. Err.    [95% Conf. Interval]
---------------------------+--------------------------------------------------
            Pr(onset_~e=1) |  {res} .0150168     .0039069     .0090156    .0247102

Simqi generated the following new variable(s): pi
{txt}(1 real change made)
(1 real change made)
(1 real change made)

      Quantity of Interest |     Mean       Std. Err.    [95% Conf. Interval]
---------------------------+--------------------------------------------------
            Pr(onset_~e=1) |  {res} .0153978     .0038001     .0093497     .024734

Simqi generated the following new variable(s): pi
{txt}(1 real change made)
(1 real change made)
(1 real change made)

      Quantity of Interest |     Mean       Std. Err.    [95% Conf. Interval]
---------------------------+--------------------------------------------------
            Pr(onset_~e=1) |  {res} .0159432     .0037433     .0100102    .0248179

Simqi generated the following new variable(s): pi
{txt}(1 real change made)
(1 real change made)
(1 real change made)

      Quantity of Interest |     Mean       Std. Err.    [95% Conf. Interval]
---------------------------+--------------------------------------------------
            Pr(onset_~e=1) |  {res} .0166689     .0037364      .010866    .0252029

Simqi generated the following new variable(s): pi
{txt}(1 real change made)
(1 real change made)
(1 real change made)

      Quantity of Interest |     Mean       Std. Err.    [95% Conf. Interval]
---------------------------+--------------------------------------------------
            Pr(onset_~e=1) |  {res} .0175967     .0037829     .0114645    .0262159

Simqi generated the following new variable(s): pi
{txt}(1 real change made)
(1 real change made)
(1 real change made)

      Quantity of Interest |     Mean       Std. Err.    [95% Conf. Interval]
---------------------------+--------------------------------------------------
            Pr(onset_~e=1) |  {res} .0187558     .0038905     .0124092    .0278575

Simqi generated the following new variable(s): pi
{txt}(1 real change made)
(1 real change made)
(1 real change made)

      Quantity of Interest |     Mean       Std. Err.    [95% Conf. Interval]
---------------------------+--------------------------------------------------
            Pr(onset_~e=1) |  {res} .0201843     .0040721     .0133333    .0295414

Simqi generated the following new variable(s): pi
{txt}(1 real change made)
(1 real change made)
(1 real change made)

      Quantity of Interest |     Mean       Std. Err.    [95% Conf. Interval]
---------------------------+--------------------------------------------------
            Pr(onset_~e=1) |  {res}  .021931      .004348     .0144431    .0321514

Simqi generated the following new variable(s): pi
{txt}(1 real change made)
(1 real change made)
(1 real change made)

      Quantity of Interest |     Mean       Std. Err.    [95% Conf. Interval]
---------------------------+--------------------------------------------------
            Pr(onset_~e=1) |  {res} .0240584     .0047474     .0159405    .0350401

Simqi generated the following new variable(s): pi
{txt}(1 real change made)
(1 real change made)
(1 real change made)

      Quantity of Interest |     Mean       Std. Err.    [95% Conf. Interval]
---------------------------+--------------------------------------------------
            Pr(onset_~e=1) |  {res} .0266459     .0053118     .0176753    .0387072

Simqi generated the following new variable(s): pi
{txt}(1 real change made)
(1 real change made)
(1 real change made)

      Quantity of Interest |     Mean       Std. Err.    [95% Conf. Interval]
---------------------------+--------------------------------------------------
            Pr(onset_~e=1) |  {res}  .029795     .0060976     .0193216    .0432977

Simqi generated the following new variable(s): pi
{txt}(1 real change made)
(1 real change made)
(1 real change made)

      Quantity of Interest |     Mean       Std. Err.    [95% Conf. Interval]
---------------------------+--------------------------------------------------
            Pr(onset_~e=1) |  {res} .0336345     .0071803     .0213661    .0500741

Simqi generated the following new variable(s): pi
{txt}(1 real change made)
(1 real change made)
(1 real change made)

      Quantity of Interest |     Mean       Std. Err.    [95% Conf. Interval]
---------------------------+--------------------------------------------------
            Pr(onset_~e=1) |  {res} .0383285     .0086598     .0242032    .0577454

Simqi generated the following new variable(s): pi
{txt}(1 real change made)
(1 real change made)
(1 real change made)

      Quantity of Interest |     Mean       Std. Err.    [95% Conf. Interval]
---------------------------+--------------------------------------------------
            Pr(onset_~e=1) |  {res} .0440857     .0106669     .0269065    .0677477

Simqi generated the following new variable(s): pi
{txt}(1 real change made)
(1 real change made)
(1 real change made)

      Quantity of Interest |     Mean       Std. Err.    [95% Conf. Interval]
---------------------------+--------------------------------------------------
            Pr(onset_~e=1) |  {res} .0511701     .0133715     .0297649    .0801133

Simqi generated the following new variable(s): pi
{txt}(1 real change made)
(1 real change made)
(1 real change made)

      Quantity of Interest |     Mean       Std. Err.    [95% Conf. Interval]
---------------------------+--------------------------------------------------
            Pr(onset_~e=1) |  {res} .0599144     .0169923     .0328072    .0981608

Simqi generated the following new variable(s): pi
{txt}(1 real change made)
(1 real change made)
(1 real change made)

      Quantity of Interest |     Mean       Std. Err.    [95% Conf. Interval]
---------------------------+--------------------------------------------------
            Pr(onset_~e=1) |  {res} .0707326     .0218028     .0360282    .1187615

Simqi generated the following new variable(s): pi
{txt}(1 real change made)
(1 real change made)
(1 real change made)

{com}. sort ageaxis
{txt}
{com}. capture drop ageaxislbl
{txt}
{com}. gen ageaxislbl=ageaxis/10
{txt}(6598 missing values generated)

{com}. graph twoway (scatter pavg ageaxislbl, connect(l) s(i) lwidth(medthick)) (rcap plo phi ageaxislbl), ///
> xtitle("Regional Relative Deprivation (Assets)") ytitle("pr(Conflict Onset)/Year ") legend( off)
{txt}
{com}. 
. 
. 
. *** FIGURE 3
. capture drop nr_X_rdrgas_c 
{txt}
{com}. gen nr_X_rdrgas_c = nr * rdrgas_c
{txt}
{com}. capture drop b1-b13
{txt}
{com}. capture drop nrplo nrphi nrpavg
{txt}
{com}. capture drop ageaxis
{txt}
{com}. capture drop pi
{txt}
{com}. estsimp logit onset_use lag_ln_dist2cic lag_ln_dist2cinc intbnd pop_use_ln ethdiff peaceyrs _spline* ///
> nr rdrgas_c nr_X, robust cl(gwno)

{txt}Iteration 0:   log pseudolikelihood = {res}-684.30126
{txt}Iteration 1:   log pseudolikelihood = {res}-677.92146
{txt}Iteration 2:   log pseudolikelihood = {res}-625.69096
{txt}Iteration 3:   log pseudolikelihood = {res}-622.98955
{txt}Iteration 4:   log pseudolikelihood = {res}-622.93493
{txt}Iteration 5:   log pseudolikelihood = {res}-622.93489

{txt}Logistic regression                               Number of obs   = {res}      6208
                                                  {txt}Wald chi2({res}12{txt})   = {res}     97.63
                                                  {txt}Prob > chi2     = {res}    0.0000
{txt}Log pseudolikelihood = {res}-622.93489                 {txt}Pseudo R2       = {res}    0.0897

                                  {txt}(Std. Err. adjusted for {res}22{txt} clusters in gwno)
{hline 13}{c TT}{hline 64}
             {c |}               Robust
   onset_use {c |}      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
{hline 13}{c +}{hline 64}
lag_ln_di~ic {c |}  {res}  .010056   .0644984     0.16   0.876    -.1163585    .1364705
{txt}lag_ln_di~nc {c |}  {res}-.0762816    .039865    -1.91   0.056    -.1544155    .0018524
      {txt}intbnd {c |}  {res}-.2442167   .3396591    -0.72   0.472    -.9099363    .4215029
  {txt}pop_use_ln {c |}  {res} .0094595   .1658812     0.06   0.955    -.3156616    .3345807
     {txt}ethdiff {c |}  {res}-.0019938   .3848201    -0.01   0.996    -.7562273    .7522397
    {txt}peaceyrs {c |}  {res} .1841937   .1733298     1.06   0.288    -.1555265    .5239138
    {txt}_spline1 {c |}  {res}   .00513   .0029075     1.76   0.078    -.0005686    .0108286
    {txt}_spline2 {c |}  {res}-.0028519    .002513    -1.13   0.256    -.0077773    .0020735
    {txt}_spline3 {c |}  {res} .0001885   .0014695     0.13   0.898    -.0026917    .0030688
          {txt}nr {c |}  {res} .7037128    .303111     2.32   0.020     .1096261      1.2978
    {txt}rdrgas_c {c |}  {res} .1278256   .2940043     0.43   0.664    -.4484121    .7040634
{txt}nr_X_rdrga~c {c |}  {res} .8439407    .362065     2.33   0.020     .1343063    1.553575
       {txt}_cons {c |}  {res}-2.638748   2.435588    -1.08   0.279    -7.412412    2.134916
{txt}{hline 13}{c BT}{hline 64}

{res}Simulating main parameters.  Please wait....
% of simulations completed: 7% 15% 23% 30% 38% 46% 53% 61% 69% 76% 84% 92% 100% 

Number of simulations  : 1000
Names of new variables : b1 b2 b3 b4 b5 b6 b7 b8 b9 b10 b11 b12 b13
{txt}
{com}. generate nrplo = .
{txt}(6626 missing values generated)

{com}. generate nrpavg = .
{txt}(6626 missing values generated)

{com}. generate nrphi = .
{txt}(6626 missing values generated)

{com}. generate ageaxis = _n - 9 in 1/23
{txt}(6603 missing values generated)

{com}. setx mean 
{txt}
{com}. local a = -8
{txt}
{com}. while `a' <= 19 {c -(}
{txt}  2{com}.         local b = (`a' - 2)/10
{txt}  3{com}.         setx rdrgas_c `b' nr 1 nr_X `b'
{txt}  4{com}.         simqi, prval(1) genpr(pi)
{txt}  5{com}.         _pctile pi, p(10,50,90)
{txt}  6{com}.         replace nrplo = r(r1) if ageaxis==`a'
{txt}  7{com}.         replace nrpavg = r(r2) if ageaxis==`a'
{txt}  8{com}.         replace nrphi = r(r3) if ageaxis==`a'
{txt}  9{com}.         drop pi
{txt} 10{com}.         local a = `a' + 1
{txt} 11{com}. {c )-}

{txt}      Quantity of Interest |     Mean       Std. Err.    [95% Conf. Interval]
---------------------------+--------------------------------------------------
            Pr(onset_~e=1) |  {res} .0128032     .0088411     .0032098    .0349868

Simqi generated the following new variable(s): pi
{txt}(1 real change made)
(1 real change made)
(1 real change made)

      Quantity of Interest |     Mean       Std. Err.    [95% Conf. Interval]
---------------------------+--------------------------------------------------
            Pr(onset_~e=1) |  {res} .0138049       .00894     .0037531    .0355243

Simqi generated the following new variable(s): pi
{txt}(1 real change made)
(1 real change made)
(1 real change made)

      Quantity of Interest |     Mean       Std. Err.    [95% Conf. Interval]
---------------------------+--------------------------------------------------
            Pr(onset_~e=1) |  {res} .0149072     .0090501     .0043118    .0369256

Simqi generated the following new variable(s): pi
{txt}(1 real change made)
(1 real change made)
(1 real change made)

      Quantity of Interest |     Mean       Std. Err.    [95% Conf. Interval]
---------------------------+--------------------------------------------------
            Pr(onset_~e=1) |  {res} .0161215     .0091739     .0051032    .0384249

Simqi generated the following new variable(s): pi
{txt}(1 real change made)
(1 real change made)
(1 real change made)

      Quantity of Interest |     Mean       Std. Err.    [95% Conf. Interval]
---------------------------+--------------------------------------------------
            Pr(onset_~e=1) |  {res} .0174602     .0093156      .005854    .0397008

Simqi generated the following new variable(s): pi
{txt}(1 real change made)
(1 real change made)
(1 real change made)

      Quantity of Interest |     Mean       Std. Err.    [95% Conf. Interval]
---------------------------+--------------------------------------------------
            Pr(onset_~e=1) |  {res} .0189375     .0094812     .0068486    .0416304

Simqi generated the following new variable(s): pi
{txt}(1 real change made)
(1 real change made)
(1 real change made)

      Quantity of Interest |     Mean       Std. Err.    [95% Conf. Interval]
---------------------------+--------------------------------------------------
            Pr(onset_~e=1) |  {res} .0205689     .0096794     .0078654     .044002

Simqi generated the following new variable(s): pi
{txt}(1 real change made)
(1 real change made)
(1 real change made)

      Quantity of Interest |     Mean       Std. Err.    [95% Conf. Interval]
---------------------------+--------------------------------------------------
            Pr(onset_~e=1) |  {res}  .022372     .0099226     .0089403    .0458638

Simqi generated the following new variable(s): pi
{txt}(1 real change made)
(1 real change made)
(1 real change made)

      Quantity of Interest |     Mean       Std. Err.    [95% Conf. Interval]
---------------------------+--------------------------------------------------
            Pr(onset_~e=1) |  {res} .0243662     .0102277     .0100879    .0478836

Simqi generated the following new variable(s): pi
{txt}(1 real change made)
(1 real change made)
(1 real change made)

      Quantity of Interest |     Mean       Std. Err.    [95% Conf. Interval]
---------------------------+--------------------------------------------------
            Pr(onset_~e=1) |  {res} .0265732     .0106172     .0112878    .0513626

Simqi generated the following new variable(s): pi
{txt}(1 real change made)
(1 real change made)
(1 real change made)

      Quantity of Interest |     Mean       Std. Err.    [95% Conf. Interval]
---------------------------+--------------------------------------------------
            Pr(onset_~e=1) |  {res} .0290172     .0111197     .0126193    .0545686

Simqi generated the following new variable(s): pi
{txt}(1 real change made)
(1 real change made)
(1 real change made)

      Quantity of Interest |     Mean       Std. Err.    [95% Conf. Interval]
---------------------------+--------------------------------------------------
            Pr(onset_~e=1) |  {res} .0317248     .0117712     .0143021    .0593848

Simqi generated the following new variable(s): pi
{txt}(1 real change made)
(1 real change made)
(1 real change made)

      Quantity of Interest |     Mean       Std. Err.    [95% Conf. Interval]
---------------------------+--------------------------------------------------
            Pr(onset_~e=1) |  {res} .0347255     .0126137     .0158513    .0649586

Simqi generated the following new variable(s): pi
{txt}(1 real change made)
(1 real change made)
(1 real change made)

      Quantity of Interest |     Mean       Std. Err.    [95% Conf. Interval]
---------------------------+--------------------------------------------------
            Pr(onset_~e=1) |  {res} .0380516      .013695     .0173739    .0709132

Simqi generated the following new variable(s): pi
{txt}(1 real change made)
(1 real change made)
(1 real change made)

      Quantity of Interest |     Mean       Std. Err.    [95% Conf. Interval]
---------------------------+--------------------------------------------------
            Pr(onset_~e=1) |  {res} .0417384      .015067     .0194713    .0775064

Simqi generated the following new variable(s): pi
{txt}(1 real change made)
(1 real change made)
(1 real change made)

      Quantity of Interest |     Mean       Std. Err.    [95% Conf. Interval]
---------------------------+--------------------------------------------------
            Pr(onset_~e=1) |  {res} .0458245     .0167834     .0212255    .0869277

Simqi generated the following new variable(s): pi
{txt}(1 real change made)
(1 real change made)
(1 real change made)

      Quantity of Interest |     Mean       Std. Err.    [95% Conf. Interval]
---------------------------+--------------------------------------------------
            Pr(onset_~e=1) |  {res} .0503511     .0188989     .0227423    .0970141

Simqi generated the following new variable(s): pi
{txt}(1 real change made)
(1 real change made)
(1 real change made)

      Quantity of Interest |     Mean       Std. Err.    [95% Conf. Interval]
---------------------------+--------------------------------------------------
            Pr(onset_~e=1) |  {res} .0553623     .0214675     .0243653    .1068991

Simqi generated the following new variable(s): pi
{txt}(1 real change made)
(1 real change made)
(1 real change made)

      Quantity of Interest |     Mean       Std. Err.    [95% Conf. Interval]
---------------------------+--------------------------------------------------
            Pr(onset_~e=1) |  {res} .0609047      .024542     .0253435    .1189613

Simqi generated the following new variable(s): pi
{txt}(1 real change made)
(1 real change made)
(1 real change made)

      Quantity of Interest |     Mean       Std. Err.    [95% Conf. Interval]
---------------------------+--------------------------------------------------
            Pr(onset_~e=1) |  {res} .0670265     .0281732     .0264304    .1328323

Simqi generated the following new variable(s): pi
{txt}(1 real change made)
(1 real change made)
(1 real change made)

      Quantity of Interest |     Mean       Std. Err.    [95% Conf. Interval]
---------------------------+--------------------------------------------------
            Pr(onset_~e=1) |  {res} .0737767     .0324089     .0275182    .1486898

Simqi generated the following new variable(s): pi
{txt}(1 real change made)
(1 real change made)
(1 real change made)

      Quantity of Interest |     Mean       Std. Err.    [95% Conf. Interval]
---------------------------+--------------------------------------------------
            Pr(onset_~e=1) |  {res} .0812043     .0372918     .0284183    .1706661

Simqi generated the following new variable(s): pi
{txt}(1 real change made)
(1 real change made)
(1 real change made)

      Quantity of Interest |     Mean       Std. Err.    [95% Conf. Interval]
---------------------------+--------------------------------------------------
            Pr(onset_~e=1) |  {res} .0893564     .0428577     .0289043    .1932296

Simqi generated the following new variable(s): pi
{txt}(1 real change made)
(1 real change made)
(1 real change made)

      Quantity of Interest |     Mean       Std. Err.    [95% Conf. Interval]
---------------------------+--------------------------------------------------
            Pr(onset_~e=1) |  {res} .0982768     .0491322     .0299237    .2167379

Simqi generated the following new variable(s): pi
{txt}(0 real changes made)
(0 real changes made)
(0 real changes made)

      Quantity of Interest |     Mean       Std. Err.    [95% Conf. Interval]
---------------------------+--------------------------------------------------
            Pr(onset_~e=1) |  {res} .1080041      .056128     .0309772    .2451337

Simqi generated the following new variable(s): pi
{txt}(0 real changes made)
(0 real changes made)
(0 real changes made)

      Quantity of Interest |     Mean       Std. Err.    [95% Conf. Interval]
---------------------------+--------------------------------------------------
            Pr(onset_~e=1) |  {res} .1185695     .0638416     .0318448    .2756403

Simqi generated the following new variable(s): pi
{txt}(0 real changes made)
(0 real changes made)
(0 real changes made)

      Quantity of Interest |     Mean       Std. Err.    [95% Conf. Interval]
---------------------------+--------------------------------------------------
            Pr(onset_~e=1) |  {res} .1299949     .0722513      .032282    .3121607

Simqi generated the following new variable(s): pi
{txt}(0 real changes made)
(0 real changes made)
(0 real changes made)

      Quantity of Interest |     Mean       Std. Err.    [95% Conf. Interval]
---------------------------+--------------------------------------------------
            Pr(onset_~e=1) |  {res} .1422908     .0813156     .0328684    .3458835

Simqi generated the following new variable(s): pi
{txt}(0 real changes made)
(0 real changes made)
(0 real changes made)

{com}. sort ageaxis
{txt}
{com}. 
. capture drop b1-b13
{txt}
{com}. capture drop no_nrplo no_nrphi no_nrpavg
{txt}
{com}. capture drop ageaxis
{txt}
{com}. capture drop pi
{txt}
{com}. estsimp logit onset_use lag_ln_dist2cic lag_ln_dist2cinc intbnd pop_use_ln ethdiff peaceyrs _spline* ///
> nr rdrgas_c nr_X, robust cl(gwno)

{txt}Iteration 0:   log pseudolikelihood = {res}-684.30126
{txt}Iteration 1:   log pseudolikelihood = {res}-677.92146
{txt}Iteration 2:   log pseudolikelihood = {res}-625.69096
{txt}Iteration 3:   log pseudolikelihood = {res}-622.98955
{txt}Iteration 4:   log pseudolikelihood = {res}-622.93493
{txt}Iteration 5:   log pseudolikelihood = {res}-622.93489

{txt}Logistic regression                               Number of obs   = {res}      6208
                                                  {txt}Wald chi2({res}12{txt})   = {res}     97.63
                                                  {txt}Prob > chi2     = {res}    0.0000
{txt}Log pseudolikelihood = {res}-622.93489                 {txt}Pseudo R2       = {res}    0.0897

                                  {txt}(Std. Err. adjusted for {res}22{txt} clusters in gwno)
{hline 13}{c TT}{hline 64}
             {c |}               Robust
   onset_use {c |}      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
{hline 13}{c +}{hline 64}
lag_ln_di~ic {c |}  {res}  .010056   .0644984     0.16   0.876    -.1163585    .1364705
{txt}lag_ln_di~nc {c |}  {res}-.0762816    .039865    -1.91   0.056    -.1544155    .0018524
      {txt}intbnd {c |}  {res}-.2442167   .3396591    -0.72   0.472    -.9099363    .4215029
  {txt}pop_use_ln {c |}  {res} .0094595   .1658812     0.06   0.955    -.3156616    .3345807
     {txt}ethdiff {c |}  {res}-.0019938   .3848201    -0.01   0.996    -.7562273    .7522397
    {txt}peaceyrs {c |}  {res} .1841937   .1733298     1.06   0.288    -.1555265    .5239138
    {txt}_spline1 {c |}  {res}   .00513   .0029075     1.76   0.078    -.0005686    .0108286
    {txt}_spline2 {c |}  {res}-.0028519    .002513    -1.13   0.256    -.0077773    .0020735
    {txt}_spline3 {c |}  {res} .0001885   .0014695     0.13   0.898    -.0026917    .0030688
          {txt}nr {c |}  {res} .7037128    .303111     2.32   0.020     .1096261      1.2978
    {txt}rdrgas_c {c |}  {res} .1278256   .2940043     0.43   0.664    -.4484121    .7040634
{txt}nr_X_rdrga~c {c |}  {res} .8439407    .362065     2.33   0.020     .1343063    1.553575
       {txt}_cons {c |}  {res}-2.638748   2.435588    -1.08   0.279    -7.412412    2.134916
{txt}{hline 13}{c BT}{hline 64}

{res}Simulating main parameters.  Please wait....
% of simulations completed: 7% 15% 23% 30% 38% 46% 53% 61% 69% 76% 84% 92% 100% 

Number of simulations  : 1000
Names of new variables : b1 b2 b3 b4 b5 b6 b7 b8 b9 b10 b11 b12 b13
{txt}
{com}. generate no_nrplo = .
{txt}(6626 missing values generated)

{com}. generate no_nrpavg = .
{txt}(6626 missing values generated)

{com}. generate no_nrphi = .
{txt}(6626 missing values generated)

{com}. generate ageaxis = _n - 9 in 1/28
{txt}(6598 missing values generated)

{com}. setx mean 
{txt}
{com}. local a = -8
{txt}
{com}. while `a' <= 19 {c -(}
{txt}  2{com}.         local b = (`a' - 2)/10
{txt}  3{com}.         setx rdrgas_c `b' nr 0 nr_X 0
{txt}  4{com}.         simqi, prval(1) genpr(pi)
{txt}  5{com}.         _pctile pi, p(10,50,90)
{txt}  6{com}.         replace no_nrplo = r(r1) if ageaxis==`a'
{txt}  7{com}.         replace no_nrpavg = r(r2) if ageaxis==`a'
{txt}  8{com}.         replace no_nrphi = r(r3) if ageaxis==`a'
{txt}  9{com}.         drop pi
{txt} 10{com}.         local a = `a' + 1
{txt} 11{com}. {c )-}

{txt}      Quantity of Interest |     Mean       Std. Err.    [95% Conf. Interval]
---------------------------+--------------------------------------------------
            Pr(onset_~e=1) |  {res} .0139463     .0075092     .0043417      .03222

Simqi generated the following new variable(s): pi
{txt}(1 real change made)
(1 real change made)
(1 real change made)

      Quantity of Interest |     Mean       Std. Err.    [95% Conf. Interval]
---------------------------+--------------------------------------------------
            Pr(onset_~e=1) |  {res} .0139384     .0070889      .004627    .0313177

Simqi generated the following new variable(s): pi
{txt}(1 real change made)
(1 real change made)
(1 real change made)

      Quantity of Interest |     Mean       Std. Err.    [95% Conf. Interval]
---------------------------+--------------------------------------------------
            Pr(onset_~e=1) |  {res}  .013941     .0066853       .00495     .030566

Simqi generated the following new variable(s): pi
{txt}(1 real change made)
(1 real change made)
(1 real change made)

      Quantity of Interest |     Mean       Std. Err.    [95% Conf. Interval]
---------------------------+--------------------------------------------------
            Pr(onset_~e=1) |  {res} .0139543     .0062977     .0053367    .0298911

Simqi generated the following new variable(s): pi
{txt}(1 real change made)
(1 real change made)
(1 real change made)

      Quantity of Interest |     Mean       Std. Err.    [95% Conf. Interval]
---------------------------+--------------------------------------------------
            Pr(onset_~e=1) |  {res} .0139782     .0059258     .0056627    .0285351

Simqi generated the following new variable(s): pi
{txt}(1 real change made)
(1 real change made)
(1 real change made)

      Quantity of Interest |     Mean       Std. Err.    [95% Conf. Interval]
---------------------------+--------------------------------------------------
            Pr(onset_~e=1) |  {res} .0140128     .0055693     .0060291    .0274659

Simqi generated the following new variable(s): pi
{txt}(1 real change made)
(1 real change made)
(1 real change made)

      Quantity of Interest |     Mean       Std. Err.    [95% Conf. Interval]
---------------------------+--------------------------------------------------
            Pr(onset_~e=1) |  {res} .0140582     .0052284      .006359    .0267217

Simqi generated the following new variable(s): pi
{txt}(1 real change made)
(1 real change made)
(1 real change made)

      Quantity of Interest |     Mean       Std. Err.    [95% Conf. Interval]
---------------------------+--------------------------------------------------
            Pr(onset_~e=1) |  {res} .0141145     .0049035     .0066693     .026113

Simqi generated the following new variable(s): pi
{txt}(1 real change made)
(1 real change made)
(1 real change made)

      Quantity of Interest |     Mean       Std. Err.    [95% Conf. Interval]
---------------------------+--------------------------------------------------
            Pr(onset_~e=1) |  {res}  .014182     .0045959     .0070229    .0252473

Simqi generated the following new variable(s): pi
{txt}(1 real change made)
(1 real change made)
(1 real change made)

      Quantity of Interest |     Mean       Std. Err.    [95% Conf. Interval]
---------------------------+--------------------------------------------------
            Pr(onset_~e=1) |  {res} .0142606     .0043071     .0074572    .0243977

Simqi generated the following new variable(s): pi
{txt}(1 real change made)
(1 real change made)
(1 real change made)

      Quantity of Interest |     Mean       Std. Err.    [95% Conf. Interval]
---------------------------+--------------------------------------------------
            Pr(onset_~e=1) |  {res} .0143507     .0040397     .0077927    .0238166

Simqi generated the following new variable(s): pi
{txt}(1 real change made)
(1 real change made)
(1 real change made)

      Quantity of Interest |     Mean       Std. Err.    [95% Conf. Interval]
---------------------------+--------------------------------------------------
            Pr(onset_~e=1) |  {res} .0144524      .003797     .0081857    .0232163

Simqi generated the following new variable(s): pi
{txt}(1 real change made)
(1 real change made)
(1 real change made)

      Quantity of Interest |     Mean       Std. Err.    [95% Conf. Interval]
---------------------------+--------------------------------------------------
            Pr(onset_~e=1) |  {res}  .014566     .0035836      .008511    .0226372

Simqi generated the following new variable(s): pi
{txt}(1 real change made)
(1 real change made)
(1 real change made)

      Quantity of Interest |     Mean       Std. Err.    [95% Conf. Interval]
---------------------------+--------------------------------------------------
            Pr(onset_~e=1) |  {res} .0146917     .0034051     .0088822    .0222899

Simqi generated the following new variable(s): pi
{txt}(1 real change made)
(1 real change made)
(1 real change made)

      Quantity of Interest |     Mean       Std. Err.    [95% Conf. Interval]
---------------------------+--------------------------------------------------
            Pr(onset_~e=1) |  {res} .0148298      .003268     .0092826    .0219534

Simqi generated the following new variable(s): pi
{txt}(1 real change made)
(1 real change made)
(1 real change made)

      Quantity of Interest |     Mean       Std. Err.    [95% Conf. Interval]
---------------------------+--------------------------------------------------
            Pr(onset_~e=1) |  {res} .0149806     .0031792     .0095612    .0219582

Simqi generated the following new variable(s): pi
{txt}(1 real change made)
(1 real change made)
(1 real change made)

      Quantity of Interest |     Mean       Std. Err.    [95% Conf. Interval]
---------------------------+--------------------------------------------------
            Pr(onset_~e=1) |  {res} .0151445     .0031452     .0098258    .0218483

Simqi generated the following new variable(s): pi
{txt}(1 real change made)
(1 real change made)
(1 real change made)

      Quantity of Interest |     Mean       Std. Err.    [95% Conf. Interval]
---------------------------+--------------------------------------------------
            Pr(onset_~e=1) |  {res} .0153219      .003171     .0099749    .0219392

Simqi generated the following new variable(s): pi
{txt}(1 real change made)
(1 real change made)
(1 real change made)

      Quantity of Interest |     Mean       Std. Err.    [95% Conf. Interval]
---------------------------+--------------------------------------------------
            Pr(onset_~e=1) |  {res}  .015513     .0032593     .0100845    .0224846

Simqi generated the following new variable(s): pi
{txt}(1 real change made)
(1 real change made)
(1 real change made)

      Quantity of Interest |     Mean       Std. Err.    [95% Conf. Interval]
---------------------------+--------------------------------------------------
            Pr(onset_~e=1) |  {res} .0157185       .00341     .0100127    .0231375

Simqi generated the following new variable(s): pi
{txt}(1 real change made)
(1 real change made)
(1 real change made)

      Quantity of Interest |     Mean       Std. Err.    [95% Conf. Interval]
---------------------------+--------------------------------------------------
            Pr(onset_~e=1) |  {res} .0159387     .0036209     .0100154    .0239285

Simqi generated the following new variable(s): pi
{txt}(1 real change made)
(1 real change made)
(1 real change made)

      Quantity of Interest |     Mean       Std. Err.    [95% Conf. Interval]
---------------------------+--------------------------------------------------
            Pr(onset_~e=1) |  {res} .0161742     .0038883     .0098821    .0246712

Simqi generated the following new variable(s): pi
{txt}(1 real change made)
(1 real change made)
(1 real change made)

      Quantity of Interest |     Mean       Std. Err.    [95% Conf. Interval]
---------------------------+--------------------------------------------------
            Pr(onset_~e=1) |  {res} .0164254     .0042082     .0095357    .0257911

Simqi generated the following new variable(s): pi
{txt}(1 real change made)
(1 real change made)
(1 real change made)

      Quantity of Interest |     Mean       Std. Err.    [95% Conf. Interval]
---------------------------+--------------------------------------------------
            Pr(onset_~e=1) |  {res} .0166931     .0045768     .0092078    .0271222

Simqi generated the following new variable(s): pi
{txt}(1 real change made)
(1 real change made)
(1 real change made)

      Quantity of Interest |     Mean       Std. Err.    [95% Conf. Interval]
---------------------------+--------------------------------------------------
            Pr(onset_~e=1) |  {res} .0169776     .0049911     .0089179    .0285692

Simqi generated the following new variable(s): pi
{txt}(1 real change made)
(1 real change made)
(1 real change made)

      Quantity of Interest |     Mean       Std. Err.    [95% Conf. Interval]
---------------------------+--------------------------------------------------
            Pr(onset_~e=1) |  {res} .0172798     .0054489     .0086569    .0301489

Simqi generated the following new variable(s): pi
{txt}(1 real change made)
(1 real change made)
(1 real change made)

      Quantity of Interest |     Mean       Std. Err.    [95% Conf. Interval]
---------------------------+--------------------------------------------------
            Pr(onset_~e=1) |  {res} .0176003     .0059489     .0083756    .0318995

Simqi generated the following new variable(s): pi
{txt}(1 real change made)
(1 real change made)
(1 real change made)

      Quantity of Interest |     Mean       Std. Err.    [95% Conf. Interval]
---------------------------+--------------------------------------------------
            Pr(onset_~e=1) |  {res} .0179398     .0064906     .0079928    .0336098

Simqi generated the following new variable(s): pi
{txt}(1 real change made)
(1 real change made)
(1 real change made)

{com}. sort ageaxis
{txt}
{com}. 
. capture drop ageaxislbl
{txt}
{com}. gen ageaxislbl=ageaxis/10
{txt}(6598 missing values generated)

{com}. version 9
{txt}
{com}. 
. capture drop var7*
{txt}
{com}. 
. gen byte var75 = 0.4 in 1
{txt}(6625 missing values generated)

{com}. gen byte var76 = 10 in 1
{txt}(6625 missing values generated)

{com}. gen str30 var77 = "Natural Resources" in 1
{txt}(6625 missing values generated)

{com}. replace var76 = 0.3 in 2
{txt}var76 was {res}byte{txt} now {res}float
{txt}(1 real change made)

{com}. replace var75 = 1.1 in 2
{txt}var75 was {res}byte{txt} now {res}float
{txt}(1 real change made)

{com}. replace var77 = "No Natural Resources" in 2
{txt}(1 real change made)

{com}. 
. for X in varlist nrp* no_nrp*: replace X = X*100

{res}->  replace nrplo = nrplo*100
{txt}(23 real changes made)

{res}->  replace nrpavg = nrpavg*100
{txt}(23 real changes made)

{res}->  replace nrphi = nrphi*100
{txt}(23 real changes made)

{res}->  replace no_nrplo = no_nrplo*100
{txt}(28 real changes made)

{res}->  replace no_nrpavg = no_nrpavg*100
{txt}(28 real changes made)

{res}->  replace no_nrphi = no_nrphi*100
{txt}(28 real changes made)

{com}. 
. graph twoway (scatter no_nrpavg ageaxislbl, connect(l) s(i) lwidth(medthick) lpattern(dash)) ///
> (scatter nrpavg ageaxislbl, connect(l) s(i) lwidth(medthick)) (rcap nrplo nrphi ageaxislbl) ///
> (rcap no_nrplo no_nrphi ageaxislbl), xtitle("Relative Deprivation (Asset)") ytitle("pr(Conflict Onset)/Year ") ///
> legend( label(1 "with Natural Resources") label(2 "without Natural Resources") label(3 "90% CI for Nat. Res.") ///
> label(4 "90% CI for No Nat. Res."))
{txt}
{com}. graph twoway (scatter no_nrpavg ageaxislbl, connect(l) s(i) lwidth(medthick)) (scatter nrpavg ageaxislbl, ///
> connect(l) s(i) lwidth(medthick)) (rcap nrplo nrphi ageaxislbl) (rcap no_nrplo no_nrphi ageaxislbl) ///
> (scatter var76 var75, s(i) mlabel(var77) legend(off)), xtitle("Regional Relative Deprivation (Assets)") ///
> ytitle("pr(Conflict Onset)/Year ") legend( label(1 "with Natural Resources") label(2 "without Natural Resources") ///
> label(3 "90% CI for Nat. Res.") label(4 "90% CI for No Nat. Res."))
{txt}
{com}. 
. version 7
{txt}
{com}. graph nrplo nrphi no_nr* ageaxis, s(iiii) c(||||)
{txt}
{com}. version 9
{txt}
{com}. 
. 
. 
. *** APPENDIX B
. sum onset_use lag_ln_dist2cic lag_ln_dist2cinc intbnd dia_sec peton_use pop_use_ln ethdiff nr asset ///
> education rdrgas rdrged asset_gini education_gini elf_reg

{txt}    Variable {c |}       Obs        Mean    Std. Dev.       Min        Max
{hline 13}{c +}{hline 56}
   onset_use {c |}{res}      6208    .0231959    .1505373          0          1
{txt}lag_ln_di~ic {c |}{res}      6626    12.43848    4.139268          0   13.97591
{txt}lag_ln_di~nc {c |}{res}      6626    11.63028    4.622104          0   14.81517
      {txt}intbnd {c |}{res}      6626    .5932689     .491261          0          1
     {txt}dia_sec {c |}{res}      6626    .1355267    .3423111          0          1
{txt}{hline 13}{c +}{hline 56}
   peton_use {c |}{res}      6626    .0834591    .2765958          0          1
  {txt}pop_use_ln {c |}{res}      6626    12.98394    1.491102   4.007333   16.55818
     {txt}ethdiff {c |}{res}      6626    .6614851    .4732403          0          1
          {txt}nr {c |}{res}      6626    .2161183     .411627          0          1
       {txt}asset {c |}{res}      6626    .2156456    .1142387   .0301587   .6502836
{txt}{hline 13}{c +}{hline 56}
   education {c |}{res}      6626     2.83325    2.441315        .01   9.666667
      {txt}rdrgas {c |}{res}      6626    .2029904    .4363266  -.7622771    1.81242
      {txt}rdrged {c |}{res}      6626    .4015052    .8078924  -1.065264   5.205451
  {txt}asset_gini {c |}{res}      6626    .4894826    .1398642     .16253     .89284
{txt}education_~i {c |}{res}      6626    .6722306     .245821          0     .98864
{txt}{hline 13}{c +}{hline 56}
     elf_reg {c |}{res}      6531    .3602347    .2304639          0   .7975872
{txt}
{com}. 
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{txt}end of do-file

{com}. log close
       {txt}log:  {res}G:\ISQ\g�_rn_jkr_ISQ_replication.smcl
  {txt}log type:  {res}smcl
 {txt}closed on:  {res} 7 Aug 2008, 16:14:21
{txt}{.-}
{smcl}
{txt}{sf}{ul off}